Monthly Archives: April 2017

Amazon Web Services and Merck announced a developer competition on Monday to that plans to harness artificial intelligence for diabetics.

Dubbed the Alexa Diabetes Challenge, and powered by Luminary Labs, the contest aims to incent upstarts and individual developers to create apps that harness Amazons Alexa voice-enabled technologies particularly for patients recently diagnosed with Type 2 diabetes.

Early adopters such as Penn Medicine and Commonwealth Care Alliance are already running proofs-of-concept or pilot programs with Amazon Alexa being the centerpiece of improving patient experience.

[Also:Hospitals forging patient experience of the future with voice AI technologies]

Whats more, a new Healthcare IT News and HIMSS Analytics HIT Market Indicator report found that half of hospitals intend to adopt some fashion of AI in five years and more than a third plan to do so within two years.

The Amazon and Merck contest enables innovators to use not only Alexa but also Amazon Web Services cloud infrastructure.

Five entrants will be chosen in the first round. Those winners will collect $25,000 and 100,000 AWS credits apiece and move into the Virtual Accelerator to access mentors as they work to transform the initial concepts into real solutions, the companies said.

[Also:AI, machine learning will shatter Moore's Law in rapid-fire pace of innovation]

The accelerator work will culminate with the finalists presenting their apps to judges in a pop-up AWS loft in New York City, after which the winner will be awarded $125,000.

At the end of the Virtual Accelerator, finalists will present their solutions in-person to the judges at Demo Day at the AWS Pop-up loft in NYC.

Submissions take place at alexadiabeteschallenge.com and close on May 22, 2017.

Twitter: @SullyHIT

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Artificial intelligence developer contest puts Alexa to the test - Healthcare IT News

A piece of digital art by Alexander Reben, an artist and roboticist interested in human-machine relationships. He ran an episode of Bob Ross' classic painting show through an artificial learning machine that tried to find images that are not there.

Alexander Reben is an artist and roboticist interested in the relationship between humans and machines. Recently, he ran an episode of Bob Ross classic public television painting show The Joy of Painting through an artificial learning system. The machine tried to find images that werent there. As Reben puts it:

This artwork represents what it would be like for an AI to watch Bob Ross on LSD (once someone invents digital drugs). It shows some of the unreasonable effectiveness and strange inner workings of deep learning systems. The unique characteristics of the human voice are learned and generated as well as hallucinations of a system trying to find images which are not there.

The results, overlaid over the original episode with clipped audio, are hypnotic and disturbing. The resulting five-minute video is on Vimeo as Deeply Artificial Trees.

Deeply Artificial Trees from artBoffin on Vimeo.

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Artificial intelligence watches Bob Ross paint and the results are disturbing - The Bozeman Daily Chronicle (blog)

Researchers highlight the 'dark side' ofAI and question whether humanity can ever truly understand its most advanced creations

WHAT sets humansapart from machines is the speed at which we can learn from our surroundings.

But scientists have successfully trained computers to use artificial intelligence to learn from experience and one day they could be smarter than their creators.

Now scientists have admitted they are already baffled by the mechanical brains they have built, raising the prospect that we could lose control of them altogether.

Computers are already performing incredible feats such as driving cars and predicting diseases but their makers say they arent entirely in control of their creations.

This could have catastrophic consequences for civilisation, tech experts have warned.

Take thestrange driverless car which appeared on the streets of New Jersey, US, last year.

It differed fromGoogle, Tesla or Ubers autonomous vehicles, which follow the rules set by tech developers to react to scenarios while on the road.

This car couldmake its own decisions after watching how humans learnt how to drive.

And itscreators, researchers at chip making company Nvidia (who supply some of the biggest car makers with supercomputer chips), said they werent 100 per cent sure how it did so, MIT Technology Review reported.

Its mysterious mind could be a sign of dark times to come, sceptics fear.

The cars underlying technology, dubbed deep learning, is a powerful tool for solving problems.

It helps us tag our friends on Facebook, provides assistance on our smartphones using Siri, Cortana or Google.

Deep learning has helpedcomputers get better at recognising objects than a person.

The military is pouring millions into the technology so it can be used to steer ships, control drones and destroy targets.

And theres hope it will be able to diagnose deadly diseases, make traders billionaires by reading the stock market and totally transform the world we live in.

But if we dont make sure creators have a full understanding of how it works, were in deep trouble, scientists claim.

Scientists have been training computers how to learn, like humans, since the 1970s.

But recent advances in data storage mean that the process has sped up exponentially in recent years.

Interest in the field hit a peak when Google paid hundreds of millions to buy a British deep learning company in 2015.

Coined machine learning or a neural network, deep learning is effectively training a computer so it can figure out natural language and instructions.

Its fed information and is then quizzed on it, so it can learn, similarly to a child in the early years at at school.

If they cant figure out how the algorithms (the formulaswhich keep computers performing the tasks we ask them to do) work, they wont be able to predict when they fail.

Tommi Jaakkola, a professor at MIT who works on applications of machine learning warns: If you had a very small neural network [deep learning algorithm], you might be able to understand it.

But once it becomes very large, and it has thousands of units per layer and maybe hundreds of layers, then it becomes quite un-understandable.

That means a driverless car, like Nvidias, could soar headfirst into a tree and we would have no idea why it decided to do so.

Just imagine if artificial intelligence was given control of the stock market or military systems.

Another computer was also tasked with analysing patient records to predict disease.

Joel Dudley, who led the project at New Yorks Mount Sinai Hospital, said the machine was inexplicably good at recognising schizophrenia but no-one knew why.

We can build these models, but we dont know how they work, he said.

Several big technology firms have been asked to be more transparent about how they create and apply deep learning.

This includes Google, which said it would create an AI ethics boardbut has kept mysteriously quiet about its existence.

A top Britishastronomer recently warnedthat humans will be wiped outby robots who will take over the earth in a matter of centuries.

He claims aliens could already be remnants of a human-like civilisation which have evolved into artificially intelligent machines.

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Humanity is already losing control of artificial intelligence and it ... - The Sun

About 35 percent of healthcare organizations plan to leverage artificial intelligence within two years and more than half intend to do so within five.

Thats according to the Healthcare IT News and HIMSS Analytics HIT Market Indicator: Artificial Intelligence.

[Also:AI, machine learning will shatter Moore's Law in rapid-fire pace of innovation]

If you look at those with plans to leverage AI in some way, shape or form, were going to see significant growth, said Brendan FitzGerald, director of research at HIMSS Analytics.

While only 4.7 percent of the 85 survey respondents are already using AI technologies, the future looks promising. Indeed, 10.6 percent plan to adopt them within 12 months, 23.5 percent indicated they will within two years and another 24.7 percent in three to five years.

Participants ranked population health, clinical decision support, patient diagnosis and precision medicine, respectively, as the top places AI will have the most substantial initial impact.

Other areas include hospital and physician workflow, security, revenue cycle and drug discovery.

As with most emerging technologies, of course, there are barriers to adopting AI. Chief among those is the feeling that AI technologies are still in early stages of development and a difficulty understanding the immediate opportunities.

[Also:More than half of hospitals hit with ransomware in last 12 months]

There are a number of technologies that require considerable fine-tuning for the healthcare space and I dont think AI is any different, FitzGerald said.

FitzGerald cautioned that vendors will be trying to keep pace with the AI gold rush the way many did with population health and telemedicine to show theyre on top of the latest and greatest technologies in healthcare and ahead of where people are going, even some who are not actually AI companies.

[Also:Hospitals rank population health, value-based care, patient experience as top strategic drivers of precision medicine]

Once the industry has a handle on how to implement AI at the point of care, Fitzgerald said, the ability for AI to present clear and present opportunities may escalate adoption.

Healthcare IT News and HIMSS Analytics are collaborating on HIT Market Indicator studies to highlight hot button issues across the healthcare IT landscape. This survey comprised responses from CEOs, CIOs, CFOs, COOs, chief medical information officers, chief clinical officers, as well as professionals working at the IT-director level and above.

Twitter: @SullyHIT

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Half of hospitals to adopt artificial intelligence within 5 years - Healthcare IT News

SAN FRANCISCO, April 11, 2017 /PRNewswire/ -- Package holiday specialists TravelBird have announced that starting April, 2017, they will partner with DigitalGenius to provide Artificial Intelligence (AI) for customer service.

TravelBird receives 900,000 incoming traveler questions per year, answered in 11 countries by email, phone, social media and SMS. To manage an increasing volume of queries while increasing customer satisfaction, TravelBird looked to new computer technology to do what it does best: taking charge of repetitive tasks like tagging and answering frequently asked questions while learning to predict answers based on historical data. These procedures enable travel and booking associates to spend more time deeply engaging with customers for a more rewarding experience on both ends.

DigitalGenius is providing TravelBird booking associates with an AI assistant to cut down on repetitive daily tasks, creating a layer of machine intelligence to enhance the quality and productivity of customer service experiences. The DigitalGenius Human+AI Platform is trained on historical customer service logs and provides AI-powered macro suggestions, automation of ticket tagging, auto-triaging, as well as automation of responses. This combination of human and machine intelligence helps customer service teams support increasing volumes faster, while unlocking more time for complex cases and meaningful conversations with customers.

TravelBird anticipates the use of AI systems will improve post-contact customer satisfaction and increase productivity while creating a more satisfying work experience for travel and booking associates.

"At TravelBird, we believe that every traveler deserves a wonderful, memorable holiday, and that sometimes, people are in need of guidance on the road," says Symen Jansma, CEO and Founder of TravelBird. "We want to better serve our travelers every day, which means quick response times for traveler queries and personalized service. With our partnership with DigitalGenius, we let computers do what they do best and leave the work involving real human connection to our experts."

Rapid growth of TravelBird's business, has led to a massive increase in message volume. Instead of replacing customer service agents with bots or moving them to a more cost effective location, they have chosen to implement DigitalGenius AI in conjunction with Zendesk as a way to make their existing team more efficient while maintaining and improving the quality of the customer service experience.

"We are thrilled to see our AI products used inside customer service centers to empower professionals working in this space, and unlocking valuable time to conduct a much higher level of service," says Mikhail Naumov, Co-founder & CSO at DigitalGenius. "TravelBird is a fantastic company with an admirable commitment to serving its customers and travelers."

To measure progress, an analytics tool will measure the number of predictions and the percentage of accuracy of the AI models. In the future, TravelBird expects AI to be widely used in all large companies to meet increasing customer service demands.

About TravelBird: TravelBird brings you the best holiday experiences, both for short breaks and international get-aways. They make a personalized selection of offers to bring you the perfect travel experience. Their aim is to make travelers discover something new through various holiday proposals, whilst their range of choices will also help you immerse into new cultures. For more information, please visit: https://travelbird.nl

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About DigitalGenius: DigitalGenius brings practical applications of artificial intelligence into the customer service operations of growing companies. Its Human+AI Customer Service Platform combines the best of human & machine intelligence, enabling companies to live up to and exceed rising customer expectations. At its core are deep-learning algorithms, which are trained on historical customer service logs and integrated directly into the contact center's existing software. Once enabled, the platform automates and increases the quality and efficiency of customer service conversations across text-based communication channels like email, chat, social media and mobile messaging. For more information, please visit http://www.digitalgenius.com

To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/how-artificial-intelligence-will-improve-traveler-experience-with-travelbird-300438403.html

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How Artificial Intelligence will Improve Traveler Experience with TravelBird - Yahoo Finance

Artificial intelligence (AI) is having a huge impact on businesses in a variety of industries, including high tech. ServiceMax, a company that provides cloud-based field service software to help organizations manage contracts, scheduling, and parts, is a case in point.

"We're constantly exploring different options and paths to incorporate artificial intelligence and machine learning into our product offering," said Indresh Satyanarayana, chief architect at ServiceMax, which was acquired by GE Digital in November 2016 to enhance is Industrial Internet of Things (IIoT) capabilities in field service.

"For the field service industry in particular, AI holds interesting implications for changing how we operate our businesses," Satyanarayana said. "We already see the practical applicability in many different areas of AI -- from enabling natural language processing in our mobile applications to realizing autonomous field work by enabling AI-based decision making."

In servicing equipment and keeping it running right, AI has the ability to directly impact how field technicians complete jobs and managers optimize work processes, Satyanarayana said.

The creation of a product that leverages AI and machine learning faces a host of challenges, however. Understanding how humans and machines can work together is never going to be easy, Satyanarayana said.

"AI and machine learning concepts operate at a fundamental level in product and feature design, and can sometimes lead to false positives if the data being fed into it isn't robust," Satyanarayana said. "We can't treat those concepts as peripheral utilities or one-trick ponies. Instead, we must take a holistic view of how we can enable them in our products."

In addition, AI and machine learning take a somewhat tangential approach compared with conventional software design and development. "The mindset shift has to happen sooner," he said.

AI has been gaining buzz for many months, but before jumping in headfirst into it, companies need to consider a few different areas of their business and whether AI will work for them, Satyanarayana said.

"The success of AI counts on the quality of the data that's fed through its system, but the magnitude, depth, and heterogeneity of it gets multiplied in the context of field service," Satyanarayana said. "No two businesses execute their processes in the same way -- especially in field service -- so it's important to make sure that your data is understood in a particular context and the insights derived from it can cater to both the process and the business."

Furthermore, individuals with different roles come and go through the flow of AI-supported programs, whether that's technicians in the field with mobile devices, back office users, dispatchers, or others. "Even machines are connected to enterprise systems" via the Internet of Things (IoT), Satyanarayana said. "It's difficult to make the engagement across all of these moving parts optimized based on continuous feedback mechanisms."

Finally, because decisions are made on account of data, making sure the decisions made by AI are accurate is crucial. "It impacts the evolution of field service organizations, whether that's how a field tech is dispatched or whether a larger business process is deployed," Satyanarayana said.

"These decisions must be made by an intelligent system, even if it's artificial. So, while enterprise data is valuable, it's tough to make computers process data the same way that people do. It takes a major mindset change that isn't always straightforward for organizations."

VIDEO: DeepMind and healthcare: How is the NHS using AI?

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Artificial intelligence: Lessons from the field | ZDNet - ZDNet